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Record W4401088833 · doi:10.18280/acsm.480308

Synthesis and Characterization of Co2O3 Thin Films by Pulsed Laser Deposition Method and Investigation Zscan and Gas Sensing Applications

2024· article· en· W4401088833 on OpenAlexvenueno aff
Manar. Lo. Dayekh, Amin Ghadi, Saleem Azara Hussain

Bibliographic record

VenueAnnales de Chimie Science des Matériaux · 2024
Typearticle
Languageen
FieldEngineering
TopicGas Sensing Nanomaterials and Sensors
Canadian institutionsnot available
Fundersnot available
KeywordsCharacterization (materials science)Pulsed laser depositionMaterials scienceDeposition (geology)Thin filmOptoelectronicsLaserNanotechnologyAnalytical Chemistry (journal)OpticsEnvironmental chemistryChemistryGeologyPhysics

Abstract

fetched live from OpenAlex

In this study, cobalt oxide Nano films were fabricated by pulsed laser deposition method on glass substrates.The structures of the cobalt oxide thin films were investigated FE-SEM images showed spherical nanoparticles with a diameter of (10-28 nm) and the particles appeared in the case of clustered pushes, and the absorption spectra showed a strong peak in the ultraviolet region at 300 nm.The result of the third-order nonlinear optical properties of cobalt oxide films also showed saturated absorption and nonlinear concentration.Thus, the cobalt oxide Nano films possess good features in nonlinear applications.The electrical features of the cobalt oxide films improved highly.The Nano films also showed NO2 sensing activity (29%, 25%, 24%) at temperatures (200, 250, 300℃) respectively.The result showed that cobalt oxide Nano films can be used in a wide range of applications.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.014
GPT teacher head0.232
Teacher spread0.218 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2024
Admission routes1
Has abstractyes

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